Abstract: |
Most regional empirical analyses are limited by the lack of data. Researchers
have to use information that is structured in administrative or political
regions which are not always economically meaningful. The non-availability of
geographically disaggregated information prevents to obtain empirical evidence
in order to answer some relevant questions in the field of urban and regional
economics. The objective of this paper is to suggest an estimation procedure,
based on entropy econometrics, which allows for inferring disaggregated
information on local income from more aggregated data. In addition to a
description of the main characteristics of the proposed technique, the paper
illustrates how the procedure works taking as an empirical application the
estimation of income for different classes of Mexican municipalities. It would
be desirable to apply the suggested technique to a study case where some
observable data are available and confront the estimates with the actual
observations. For this purpose, we have taken the information contained in the
Mexican census as a benchmark for our estimation technique. Assuming that the
only available data are the income aggregates per type of municipality and
State, we make an exercise of ecological inference and disaggregate these
margins to recover individual (local) data. |